soft robotic manipulation of onions and artichokes in the food industry

This paper presents the development of a robotic solution for a problem of fast manipulation and handling of onions or artichokes in the food industry. The complete solution consists of a parallel robotic manipulatior, a specially designed end-effector based on a customized vacuum suction cup, and a computer vision software developed for pick and place operations. First, the selection and design process of the proposed robotic solution to fit with the initial requeriments is presented, including the customized vacuum suction cup. Then, the kinematic analysis of the parallel manipulator needed to develop the robot control system is reviewed. Moreover, computer vision application is presented inthe paper. Hardware details of the implementation of the building prototype are also shown. Finally, conclusions and future work show the current status of the project

First results of the ROSEBUD Dark Matter experiment

Rare Objects SEarch with Bolometers UndergrounD) is an experiment which attempts to detect low mass Weak Interacting Massive Particles (WIMPs) through their elastic scattering off Al and O nuclei. It consists of three small sapphire bolometers (of a total mass of 100 g) with NTD-Ge sensors in a dilution refrigerator operating at 20 mK in the Canfranc Underground Laboratory. We report in this paper the results of several runs (of about 10 days each) with successively improved energy thresholds, and the progressive background reduction obtained by improvement of the radiopurity of the components and subsequent modifications in the experimental assembly, including the addition of old lead shields. Mid-term plans and perspectives of the experiment are also presented.Comment: 14 pages, 8 figures, submitted to Astroparticle Physic

Improving the activity in hydrodechlorination of Pd/C catalysts by nitrogen doping of activated carbon supports

Aqueous phase 4-chlorophenol hydrodechlorination reaction was used to study the effect of N-doping of activated carbon support on the catalytic activity of Pd catalysts. Activated carbon was doped using pyridine and 1,10-phenantroline, reaching nitrogen contents of 0.42-1.22 and 1.35-4.19 % (w), respectively. All catalysts (0.75 % Pd w, carbon basis) showed relatively large Pd nanoparticles (35-55nm), but they exhibited fast and complete 4-chlorophenol disappearance in batch experiments. In runs at 30°C 4-chlorophenol disappearance was mainly ascribed to hydrodechlorination, although N-doping of the support also increased adsorption. Catalysts with supports doped with pyridine yielded higher 4-chlorophenol disappearance rate in spite of lower bulk nitrogen content, however they showed higher concentration of nitrogen species at the external surface and lower loss of surface area during the doping. 4-chlorophenol disappearance rate was boosted at 60°C, with minor differences between catalysts with undoped and N-doped supports, but generation of cyclohexanone was only observed for the ones with doped support. Phenol generation simultaneous to 4-chlorophenol disappearance was observed with all the catalysts. However, subsequent hydrogenation to cyclohexanone ocurred only with the catalysts supported on N-doped activated carbonThe authors greatly appreciate the financial support of this research from the Spanish Ministry of Economy and Competitiveness through the project CTQ2012-3282

Auto-adaptative Robot-aided Therapy based in 3D Virtual Tasks controlled by a Supervised and Dynamic Neuro-Fuzzy System

This paper presents an application formed by a classification method based on the architecture of ART neural network (Adaptive Resonance Theory) and the Fuzzy Set Theory to classify physiological reactions in order to automatically and dynamically adapt a robot-assisted rehabilitation therapy to the patient needs, using a three-dimensional task in a virtual reality system. Firstly, the mathematical and structural model of the neuro-fuzzy classification method is described together with the signal and training data acquisition. Then, the virtual designed task with physics behavior and its development procedure are explained. Finally, the general architecture of the experimentation for the auto-adaptive therapy is presented using the classification method with the virtual reality exercise

3D Bioprinting and Near-Field Electrospinning Composite Scaffolds for the Bone-Ligament Interface

3D bioprinting is an additive manufacturing technique that can utilize a range of bioactive materials to construct specific architectures that mimic native tissue. Near-field electrospinning (NFE) offers precise alignment control to create non-woven mats with high tensile strengths. We built a custom E-spin printer that enables layer-by-layer alternating deposition between 3D bioprinting and NFE to create composite scaffolds for the bone-ligament interface. This complex region is difficult to simulate due to its functionally graded mechanical and biochemical properties. We created NFE poly(caprolactone) highly aligned micro-fibers which formed collagen fibril-like bundles. Poly(ethylene glycol) diacrylate with decellularized bone was encased in the PCL fibers to create bony ligament support structures in a composite scaffold. Cytotoxicity of all materials was determined through a Live/Dead assay (Thermo Fisher) with NIH/3T3 cells. The materials and the composite scaffold were seeded with 3T3 cells and cultured for three days before undergoing an immunocytochemistry staining (ICC) to assess cell adhesion and spreading. Increased adhesion and spreading on decellularized bone scaffolds along with cell elongation in the direction of the fibers suggests the ability of the scaffold to encourage osteoblastic differentiation and ligamentous tissue formation, though a longitudinal study is still underway. Mechanical results suggest that the composite scaffolds have increased compressive strength over PEGDA alone as the PCL fibers constrict horizontal elongation, thus yielding a higher compressive modulus. The PCL fibers demonstrated a tensile strength approaching native ligament (3.96 ± 1.10 MPa), which shows promise as the ligament phase of the scaffold. The E-spin printer’s versatility with materials of disparate viscosities enabled the layer-by-layer fabrication of composite (PCL/PEGDA+bone) scaffolds that begin to mimic the complex nature of the bone-ligament interface

Understanding the mechanisms of lung mechanical stress

Physical forces affect both the function and phenotype of cells in the lung. Bronchial, alveolar, and other parenchymal cells, as well as fibroblasts and macrophages, are normally subjected to a variety of passive and active mechanical forces associated with lung inflation and vascular perfusion as a result of the dynamic nature of lung function. These forces include changes in stress (force per unit area) or strain (any forced change in length in relation to the initial length) and shear stress (the stress component parallel to a given surface). The responses of cells to mechanical forces are the result of the cell's ability to sense and transduce these stimuli into intracellular signaling pathways able to communicate the information to its interior. This review will focus on the modulation of intracellular pathways by lung mechanical forces and the intercellular signaling. A better understanding of the mechanisms by which lung cells transduce physical forces into biochemical and biological signals is of key importance for identifying targets for the treatment and prevention of physical force-related disorders

Structural basis of the pleiotropic and specific phenotypic consequences of missense mutations in the multifunctional NAD(P)H:quinone oxidoreductase 1 and their pharmacological rescue

The multifunctional nature of human flavoproteins is critically linked to their ability to populate multiple conformational states. Ligand binding, post-translational modifications and disease-associated mutations can reshape this functional landscape, although the structure-function relationships of these effects are not well understood. Herein, we characterized the structural and functional consequences of two mutations (the cancer-associated P187S and the phosphomimetic S82D) on different ligation states which are relevant to flavin binding, intracellular stability and catalysis of the disease-associated NQO1 flavoprotein. We found that these mutations affected the stability locally and their effects propagated differently through the protein structure depending both on the nature of the mutation and the ligand bound, showing directional preference from the mutated site and leading to specific phenotypic manifestations in different functional traits (FAD binding, catalysis and inhibition, intracellular stability and pharmacological response to ligands). Our study thus supports that pleitropic effects of disease-causing mutations and phosphorylation events on human flavoproteins may be caused by long-range structural propagation of stability effects to different functional sites that depend on the ligation-state and site-specific perturbations. Our approach can be of general application to investigate these pleiotropic effects at the flavoproteome scale in the absence of high-resolution structural models. © 202

Methodology for modeling and parameter estimation of the growth process of Lobesia botrana

[EN] Lobesia botrana (L. botrana), is a quarantine pest that causes damage to grapevines and generates economic losses for the region of Cuyo in Argentina. Different researchers have sought to safeguard the integrity of the vineyards, generating alert systems based on models that allow detecting the peaks of occurrence of the pest, and knowing the growth process of the moth, according to the environmental conditions of each region. In this work, a methodology for estimating unknown parameters in semi-physical models based on first principles (MSBPP) is proposed, with a particular application in the growth model of L. botrana under laboratory conditions. The main contribution consists of a methodology for parameter estimation of an MSBPP, which considers a mathematical model developed by the authors in previous work, the structural identifiability analysis of the model in question, and the estimation of the set of unknown parameters that meet the structural identifiability property. In this work, the non-linear least squares algorithm and an Extended Kalman Filter are considered the main estimation tools. An improvement in the adjustment of the mathematical model to the experimental data was evidenced, in relation to those previously obtained. In addition, the degree of affinity of each growth stage for its limiting factor was established, and new mortality profiles were presented.[ES] Lobesia botrana (L. botrana), es una plaga cuarentenaria que provoca danos a la vid, y genera perdidas económicas para la región de Cuyo en Argentina. Diferentes investigaciones han buscado salvaguardar la integridad de los viñedos, generando sistemas de alerta basados en modelos que permitan detectar los picos de ocurrencia de la plaga, y conocer el proceso de crecimiento de lapolilla, de acuerdo a las condiciones ambientales de cada región. En este trabajo, se propone una metodología para la estimación de parámetros desconocidos en los modelos semi físicos basados en primeros principios (MSBPP), con una aplicación particular en el modelo de crecimiento de L. botrana, en condiciones de laboratorio. La principal contribucion consiste en una metodología para la estimación de parámetros de un MSBPP, que considera un modelo matemático desarrollado por los autores en un trabajo previo, el análisis de identificabilidad estructural del modelo en cuestión y la estimación del conjunto de parámetros desconocidos que cumplen con la propiedad de identificabilidad estructural. En este trabajo se consideran, como herramientas principales para la estimación, el algoritmo de mínimos cuadrados no lineales, y un Filtro de Kalman Extendido. Se evidencio una mejoría en el ajuste del modelo matematico a los datos experimentales, con relación a los obtenidos previamente. Además, se estableció el grado de afinidad de cada estadio de crecimiento por el factor limitante del mismo, y se presentaron nuevos perfiles de mortalidad.Estefanía Aguirre-Zapata esta financiada por una beca doctoral latinoamericana del Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET) de Argentina, y cofinanciada por el programa ENLAZAMUNDOS de la Agencia de Educación Postsecundaria (SAPIENCIA) de Medellín, Colombia. Humberto Morales tiene una beca doctoral del Servicio de Intercambio Académico Alemán (DAAD). Los datos experimentales utilizados para el proceso de ajuste y validación del modelo fueron proveídos por el Instituto Nacional de Tecnología Agropecuaria (INTA) - Mendoza, Argentina.Aguirre-Zapata, E.; Garcia-Tirado, J.; Morales, H.; Di Sciascio, F.; Amicarelli, AN. (2022). Metodología para el modelado y la estimación de parámetros del proceso de crecimiento de Lobesia botrana. Revista Iberoamericana de Automática e Informática industrial. 20(1):68-79. https://doi.org/10.4995/riai.2022.17746687920